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Record W2116300329 · doi:10.1175/jtech-1674.1

A Laterally Averaged Nonhydrostatic Ocean Model

2004· article· en· W2116300329 on OpenAlexaff
Daniel Bourgault, Dan Kelley

Bibliographic record

VenueJournal of Atmospheric and Oceanic Technology · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsDalhousie UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsTurbulenceGeologyMechanicsHydrostatic equilibriumStratified flowsAmplitudeFrontogenesisStratified flowFlow (mathematics)MeteorologyPhysicsStatistical physicsClimatologyMesoscale meteorology

Abstract

fetched live from OpenAlex

Abstract A laterally averaged nonhydrostatic model for stratified flow in dynamically narrow domains is presented. Averaging laterally yields the computational efficiency of a two-dimensional model, while retaining some effects associated with variable domain width, such as flow acceleration through contracting channels. The model may be run in both hydrostatic and nonhydrostatic modes, and in the latter case it converges rapidly if the flow is approximately hydrostatic. The model's strengths and weaknesses are illustrated with a series of test cases of increasing complexity. Side-by-side comparisons with laboratory observations show the ability of the model to simulate the structures of nonhydrostatic flows, including shear instabilities and overturning internal waves, with discrepancies becoming apparent mainly for transition to three-dimensional turbulence. Similar results are demonstrated in an application to the stratified sill flow in Knight Inlet, British Columbia. The model reproduces nonhydrostatic features thought to be dynamically important to this system, including the generation of large-amplitude lee waves and shear instabilities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.180
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2004
Admission routes1
Has abstractyes

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